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Optical coherence tomography (OCT) is a non-invasive imaging modality with high spatial resolution suitable for early embryonic heart imaging. However, the most commonly used OCT systems cannot provide direct 4-D imaging due to acquisition speed limitations. We proposed a retrospective gating 4-D reconstruction method based on spectral domain OCT. A special circuit was designed to measure the impedance change of chick embryos in response to the heart beating. The impedance signal was acquired simultaneously with the OCT B-scan image sequence at several different locations along the heart. The impedance signal was used as a gating for 4-D reconstruction. The reconstruction algorithm includes cardiac period calculation, interpolation from multi-cardiac cycle image sequence into one cardiac cycle, and cardiac phase synchronization among the different locations of the heart. The synchronism of the impedance signal change with the heartbeat was verified. Using the proposed method, we reconstructed the cardiac outflow tract (OFT) of chick embryos at an early stage of development (Hamburger–Hamilton stage 18). We showed that the reconstructed 4-D images correctly captured the dynamics of the OFT wall motion.

We introduce a method to extract the photoacoustic (PA) signal from a contrast reduction of the interference spectrum acquired by spectral domain optical coherence tomography (SDOCT). This all-optical detection is achieved in a noncontact manner directly on the water surface covered on the sample by using its specular reflection. During SDOCT exposure, the phase of the interference spectrum keeps shaking according to the water surface vibration induced by PA excitation. This results in an interference contrast reduction which is quantified by a fast Fourier transform (FFT) for PA imaging. A tungsten filament, asparagus fern leaf, and mouse auricle are imaged to demonstrate the method.

The absence of lymphatic vessels in tumors leads to the retention of interstitial fluid, and the formation of an inverse pressure difference between the tumor and blood vessels hinders drug delivery deep into the tumor, which leads to tumor recurrence and metastasis. Therefore, we designed a novel strategy to downregulate tumor interstitial fluid pressure (TIFP) by water splitting in the tumor interstitium based on piezoelectric catalysis nanomedicine. First, the chemotherapeutic drug doxorubicin (DOX) was loaded on the piezoelectric catalytic material MoS

Retinal segmentation is a prerequisite for quantifying retinal structural features and diagnosing related ophthalmic diseases. Canny operator is recognized as the best boundary detection operator so far, and is often used to obtain the initial boundary of the retina in retinal segmentation. However, the traditional Canny operator is susceptible to vascular shadows, vitreous artifacts, or noise interference in retinal segmentation, causing serious misdetection or missed detection. This paper proposed an improved Canny operator for automatic segmentation of retinal boundaries. The improved algorithm solves the problems of the traditional Canny operator by adding a multi-point boundary search step on the basis of the original method, and adjusts the convolution kernel. The algorithm was used to segment the retinal images of healthy subjects and age-related macular degeneration (AMD) patients; eleven retinal boundaries were identified and compared with the results of manual segmentation by the ophthalmologists. The average difference between the automatic and manual methods is: 2-6 microns (1~2 pixels) for healthy subjects and 3-10 microns (1~3 pixels) for AMD patients. Qualitative method is also used to verify the accuracy and stability of the algorithm. The percentage of “perfect segmentation” and “good segmentation” is 98% in healthy subjects and 94% in AMD patients. This algorithm can be used alone or in combination with other methods as an initial boundary detection algorithm. It is easy to understand and improve, and may become a useful tool for analyzing and diagnosing eye diseases.

The advancement of anti-tumor nanomedicines is restricted by the delivery efficiency owing to a lack of insight into the intratumoral delivery mechanism, especially traversing the biological barriers. Herein, we explore a new strategy focusing on controlling excessive high tumor interstitial fluid pressure (TIFP) caused by lymphatic lack, which hampers the convective diffusion of nanomedicines to the tumor center. We construct a “nano-lymphatic” system (DOX/g-C3N4/luminol@cytomembrane, DCL@M) based on graphitic carbon nitride (g-C3N4) for photocatalytic water splitting, which can decrease the volume of the tumor interstitial fluid to ameliorate the transfer resistance derived from the high TIFP. In the tumor microenvironment, lactic acid as a sacrificial agent in catalysis greatly promoted the water-splitting efficiency; thus, TIFP in the tumor tissue was reduced to 62.11%, causing an enhancement in blood perfusion to the tumor. The accumulation of the “nano-lymphatic” system (16.73%) in the tumor was 15.9- and 3.31-fold greater than those of free doxorubicin hydrochloride (DOX, 1.05%) and DOX/g-C3N4@cytomembrane (DC@M, 3.03%), respectively. The penetration efficiency of the “nano-lymphatic” system was 8.98% at the tumor center. The “nano-lymphatic” strategy produced reactive oxygen species associated with water splitting to suppress the tumor growth; thus, we define the strategy as hydrodynamic therapy, which provides a new avenue for nanomedicines in traversing biological barriers and achieves a better therapeutic effect.

In this study, convolutional neural network based on Gramian angular field (GAF-CNN) was firstly proposed. The 1-D Raman spectral data was converted into images and used for predicting the biochemical value of blood glucose. 106 sets of blood spectrums were acquired by Fourier transform (FT) Raman spectroscopy. Spectral data ranging from 800 cm

The size and shape of the foveal avascular zone (FAZ) have a strong positive correlation with several vision-threatening retinovascular diseases. The identification, segmentation and analysis of FAZ are of great significance to clinical diagnosis and treatment. We presented an adaptive watershed algorithm to automatically extract FAZ from retinal optical coherence tomography angiography (OCTA) images. For the traditional watershed algorithm, “over-segmentation” is the most common problem. FAZ is often incorrectly divided into multiple regions by redundant “dams”. This paper analyzed the relationship between the “dams” length and the maximum inscribed circle radius of FAZ, and proposed an adaptive watershed algorithm to solve the problem of “over-segmentation”. Here, 132 healthy retinal images and 50 diabetic retinopathy (DR) images were used to verify the accuracy and stability of the algorithm. Three ophthalmologists were invited to make quantitative and qualitative evaluations on the segmentation results of this algorithm. The quantitative evaluation results show that the correlation coefficients between the automatic and manual segmentation results are 0.945 (in healthy subjects) and 0.927 (in DR patients), respectively. For qualitative evaluation, the percentages of “perfect segmentation” (score of 3) and “good segmentation” (score of 2) are 99.4% (in healthy subjects) and 98.7% (in DR patients), respectively. This work promotes the application of watershed algorithm in FAZ segmentation, making it a useful tool for analyzing and diagnosing eye diseases.

Because of the deficiency of lymphatic reflux in the tumor, the retention of tumor interstitial fluid causes aggravation of the tumor interstitial pressure (TIP), which leads to unsatisfactory tumor penetration of nanomedicine. It is the main inducement of tumor recurrence and metastasis. Herein, we design a pyroelectric catalysis-based "Nano-lymphatic" to decrease the TIP for enhanced tumor penetration and treatments. It realizes photothermal therapy and decomposition of tumor interstitial fluid under NIR-II laser irradiation after reaching the tumor, which reduces the TIP for enhanced tumor penetration. Simultaneously, reactive oxygen species generated during the pyroelectric catalysis can further damage deep tumor stem cells. The results indicate that the "Nano-lymphatic" relieves 52% of TIP, leading to enhanced tumor penetration, which effectively inhibits the tumor proliferation (93.75%) and recurrence. Our finding presents a rational strategy to reduce TIP by pyroelectric catalysis for enhanced tumor penetration and improved treatments, which is of great significance for drug delivery.

We report on fabricating plasmonic nanorod crystals using focused ion beam lithography. We first demonstrate manipulating the profiles of nanorods perpendicularly aligned with the substrate. Then we show accurate control of nanorod outlines can be achieved. We also show that it is feasible to manufacture nanorods obliquely aligned with the substrate. Tunable plasmon resonance can be realized with different tilting angles and geometries. Our approach may find important applications in plasmon-assisted sensing and surface enhanced spectroscopy.

Background Ischemic cerebral edema (CE) is a major leading cause of death in patients with ischemic stroke. The CE progression is closely related to the local cerebral blood perfusion (LCBP) level surrounding the edema area. Quantitative studying the interaction between the CE and peripheral LCBP may provide new inspiration for control and even treatment of CE. Methods Photothrombosis ischemia mouse model was established and observed for 9 hours using swept-source optical coherence tomography (SS-OCT). OCT-based angiography and OCT-based attenuation imaging techniques were used to reconstruct the angiograms reflecting the cerebral blood perfusion (CBP) level and optical attenuation coefficient (OAC) maps reflecting the edema state. The influence of edema on LCBP was analyzed by quantifying the blood perfusion in different spatial locations around the edema tissue, and the influence of LCBP on CE progression was revealed by comparing the changes of the edema area and LCBP level over time. Results Preliminary studies show that the effect of edema tissue on LCBP is very significant, which shows a clear spatial dependence. LCBP near the edema tissue is 15-20% lower than that far away from the edema tissue. When the LCBP drops to around 60% of the initial value, the edema area increases sharply. In addition, the level of CBP in the contralateral hemisphere also decreases with time. When the contralateral CBP drops to around 60%, there is a certain probability that contralateral edema will occur. Conclusions CE progression is not only related to the LCBP around the edema tissue but also related to the CBP of non-edematous regions. Controlling the CBP level of non-edematous regions may play a positive role in the treatment of CE. This work provides a new method and inspiration for exploring the mechanism of ischemic CE progression.

Owing to deficiency of lymphatic reflux in the tumor, the retention of tumor interstitial fluid causes the aggravation of tumor interstitial pressure (TIP), which leads to unsatisfactory tumor penetration of nanomedicine. It is the main inducement of tumor recurrence and metastasis. Herein, we design a pyroelectric catalysis-based “Nano-lymphatic” to decrease the TIP for enhanced tumor penetration and treatments. It realizes photothermal therapy and decomposition of tumor interstitial fluid under NIR-II laser irradiation after reaching the tumor, which reduces the TIP for enhanced tumor penetration. Simultaneously, reactive oxygen species generated during the pyroelectric catalysis can further damage deep tumor stem cells. The results indicate that the “Nano-lymphatic” relieves 52% of TIP, leading to enhanced tumor penetration, which effectively inhibits the tumor proliferation (93.75%) and recurrence. Our finding presents a novel strategy to reduce TIP by pyroelectric catalysis for enhanced tumor penetration and improved treatments, which is of great significance for drug delivery.

Segmentation of layers in retinal images obtained by optical coherence tomography (OCT) has become an important clinical tool to diagnose ophthalmic diseases. However, due to the susceptibility to speckle noise and shadow of blood vessels etc., the layer segmentation technology based on a single image still fail to reach a satisfactory level. We propose a combination method of structure interpolation and lateral mean filtering (SI-LMF) to improve the signal-to-noise ratio based on one retinal image. Before performing one-dimensional lateral mean filtering to remove noise, structure interpolation was operated to eliminate thickness fluctuations. Then, we used boundary growth method to identify boundaries. Compared with existing segmentations, the method proposed in this paper requires less data and avoids the influence of microsaccade. The automatic segmentation method was verified on the spectral domain OCT volume images obtained from four normal objects, which successfully identified the boundaries of 10 physiological layers, consistent with the results based on the manual determination.

Cerebral edema is a severe complication of acute ischemic stroke with high mortality but limited treatment. Although parameters such as brain water content and intracranial pressure may represent the global assessment of edema, optical properties can appear heterogeneously throughout the cerebral tissue relative to the site of injury. In this study, we have monitored the edema formation and progression in both permanent and transient middle cerebral artery occlusion models in rats. Edema was reflected by the decrease of optical attenuation coefficient (OAC) value in OCT system. By utilizing swept-source optical coherence tomography (SS-OCT), we found that in photochemically induced permanent focal stroke model, both the edema size and edema index, steadily developed until the end of monitor (7[Formula: see text]h). Comparatively, when transient ischemia was introduced with endothelin-1 (ET-1), the edema was detected as early as 15[Formula: see text]min, and began to recover after 30[Formula: see text]min until monitor was finished (3[Formula: see text]h). Despite the majority of the edema being recovered to some extent, the condition of a small region within the edema kept deteriorating, presumably due to the reperfusion damage which might result in serious clinical outcomes. Our study has compared the edema characteristics from two different acute ischemic stroke situations. This work not only confirms the capability of OCT to temporal and spatial monitor of edema but is also able to locate focal conditions at some areas that might highly determine the prognosis and treatment decisions.

In this paper, a reagent-free simultaneous and direct detection method of three analytes in human blood based on Fourier-transform Raman (FT-Raman) spectroscopy with 1064 nm laser radiation was proposed for the first time. A total of 161 human blood samples were characterized by FT-Raman spectroscopy under the excitation laser source of 1064 nm. In order to achieve a robust regression model, the Nonlinear Iterative Partial Least Squares (NIPALS) with orthogonal signal correction (OSC) algorithm and sample set partition based on a joint x-y distance (SPXY) is used to establish multivariate calibration models. The root means square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP), correlation coefficients ( R 2 ) and ratio of performance to deviation (RPD) were 0.34255 mg/dL, 0.3662 mg/dL, 0.99982 and 56.3524 for glucose, 0.33656 mg/dL, 0.75736 mg/dL, 0.99967 and 34.9169 for total cholesterol (TC), and 0.29956 mg/dL, 0.27469 mg/dL, 0.99998 and 173.5098 for triglycerides (TG), respectively. The analysis results showed that the proposed method could be able to accurately predict the concentration of glucose, TC and TG in blood. This method can instantaneous multi-component detection on whole blood.

With the increasing capacity and transmission distance of the power grid, HVDC technology has been more and more widely used. MTDC is an essential direction for the development of HVDC technology. At this stage, LCC is widely used in the MTDC transmission project, and there is a lot of corresponding design software, but the software development of the hybrid DC transmission is not perfect and mature enough. In this paper, the design method of the parameters of the main loop in the LCC-MMC hybrid HVDC transmission system has been studied. The corresponding design software has been compiled, and this paper presents functional modules to be accomplished in the software package. The correctness of the software calculation is verified by the actual HVDC transmission project data, and the software can be applied to the initial design of the hybrid HVDC transmission project.

In this paper, a one-dimensional shallow convolutional neural network structure combined with elastic nets (1D-SCNN-EN) was firstly proposed to predict the glucose concentration of blood by Raman spectroscopy. A total of 106 different blood glucose spectra were obtained by Fourier transform (FT) Raman spectroscopy. The one-dimensional shallow convolutional neural network, with elastic nets added to the full connected layer, was presented to capture multiple deep features and reduce the complexity of the model. The 1D-SCNN-EN model has a better performance than conventional approaches (partial least squares and support vector machine). The root mean squared error of calibration (RMSEC), the root mean squared error of prediction (RMSEP), the determination coefficient of prediction ( R P 2 ), and the residual predictive deviation of prediction (RPD) were 0.10262, 0.11210, 0.99403, and 12.94601, respectively. The experiment results showed that the 1D-SCNN-EN model has a higher prediction accuracy and stronger robustness than the other regression models. The overall studies indicated that the 1D-SCNN-EN model looked promising for predict the glucose concentration of blood by Raman spectroscopy when the sample size is small.

The aim of the current research work was to develop sonophoresis-assisted transdermal patches for the treatment of osteoporosis. In the present investigation, we formulated alendronate-chitosan nanoparticles by ionotropic external gelation method. The prepared nanoparticles were found to be smooth and free-flowing. The optimized formulation showed 82.7% of drug release over a period of 12 hours with 99.54% EE, the particle size of 250 nm, PDI 0.22 and zeta potential of 28 mV. The solvent casting evaporation method was used for the development of the patches using HPMC as rate-controlling polymer and dibutyl phthalate as the plasticizer. The optimized patch formulation was found acceptable in terms of physical characteristics (appearance, thickness, folding endurance, weight variation, moisture loss and uptake). The drug content was found to be 99.66±0.9 % with 69.44% of drug permeation through the rat skin. The TP3 formulation had drug content of 99.96% which was the highest among all of the formulations and showed relatively controlled skin permeation of 69.44% over the period of 12 hours. Nearly six-time enhancement of bioavailability was observed when alendronate was used in the nanoparticulate form in transdermal patches used with sonophoresis. Over the period of seven days, the plasma calcium concentration in the rat model was decreased from 16 mg/dl to 4 mg/dl (4 times) in rat groups treated with the transdermal patches containing CS-ALN-NP while the concentration dropped only to 12 mg/dl in case of the transdermal patches containing pure Alendronate. These findings (enhanced skin permeation, enhanced bioavailability and suppression of the plasma calcium level) regarding the transdermal delivery system suggest a promising approach for the treatment of osteoporosis.

The progression of ischemic cerebral edema (CE) is closely related to the level of cerebral blood perfusion (CBP) and affects each other. Simultaneous detection of CBP and CE is helpful in understanding the mechanisms of ischemic CE development. In this article, a wide field of view swept-source optical coherence tomography system was used to detect CE status and CBP levels simultaneously in middle cerebral artery occlusion rats. Images reflecting these two physiological states can be reconstructed with only one C-scan. We quantify these two physiological states into four parameters, which contain two vascular parameters (vascular displacement distance and vascular perfusion density) and two edema parameters (optical attenuation coefficient and edema area). The association between the two vascular parameters and the two edema parameters was analyzed. The results show that there is a strong linear relationship between blood flow parameters and edema parameters. This work provides a new option for CE in vivo detection, and is very likely to play an important role in the development of relevant drugs or in selection of treatment options.

We demonstrate a 3×3 coupler-based fiber-optic interferometric system to detect the local initial photoacoustic pressure. In contrast with the existing interferometric photoacoustic microscopy (PAM) relying on the measurement of the phase change of the probe light caused by the sample surface vibration, the present method measures the intensity change of the probe light caused by the initial photoacoustic pressure. Compared with the conventional interferometric PAMs, this method has the advantages: (1) it is free from the influence of the rough tissue surface, achieving complete noncontact in vivo imaging; (2) the probe light and the excitation light are focused at a same point below the sample surface, and the confocal configuration makes it more convenient for in vivo imaging; and (3) there is no need for phase stabilization, allowing a high imaging speed. These advantages show that the method will be a promising technique for in vivo imaging. This method is verified by imaging of a resolution test target and in vivo imaging of the blood vessels in a mouse ear.

For spectroscopic measurements, representative samples are needed in the course of building a calibration model to guarantee accurate predictions. The most widely used selection method is the Kennard-Stone method, which can be used before a reference measurement is done. In this paper, a method termed semi-supervised selection is presented to determine whether a sample should be added to the calibration set. The selection procedure has two steps. First, part of the population of samples is selected using the Kennard-Stone method, and their concentrations are measured. Second, another part of the population of samples is selected based on the scalar value distribution of the net analyte signal. If the net analyte signal of a sample is distinctive compared to the existing net analyte signal values, then the sample is added to the calibration set. The analyte of interest in the sample is then measured so that the sample can be used as a calibration sample. By a validation test, it is shown that the presented method is more efficient than random selection and Kennard-Stone selection. As a result, both the time and the money spent on reference measurements are saved.